School of Management, Xuzhou Medical University, Xuzhou, Jiangsu, China.
School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China.
PLoS One. 2024 Apr 9;19(4):e0301272. doi: 10.1371/journal.pone.0301272. eCollection 2024.
In urban stochastic transportation networks, there are specific links that hold great importance. Disruptions or failures in these critical links can lead to reduced connectivity within the road network. Under this circumstance, this manuscript proposed a novel identification of critical links mathematical optimization model based on the optimal reliable path with consideration of link correlations under demand uncertainty. The method presented in this paper offers a solution to bypass the necessity of conducting a full scan of the entire road network. Due to the non-additive and non-linear properties of the proposed model, a modified heuristic algorithm based on K-shortest algorithm and inequality technical is presented. The numerical experiments are conducted to show that improve a certain road link may not necessarily improve the overall traffic conditions. Moreover, the results indicate that if the travel time reliability is not considered, it will bring errors to the identification of key links.
在城市随机交通网络中，存在特定的具有重要意义的关键链路。这些关键链路的中断或故障会导致路网连通性降低。在这种情况下，本文提出了一种基于最优可靠路径的新的关键链路识别数学优化模型，该模型考虑了需求不确定性下链路相关性。该方法提供了一种解决方案，可避免对整个路网进行全面扫描的必要性。由于所提出模型的非可加性和非线性特性，提出了一种基于 K-最短算法和不等式技术的改进启发式算法。数值实验表明，改善某条道路链路不一定能改善整体交通状况。此外，结果表明，如果不考虑旅行时间可靠性，将会对关键链路的识别带来误差。
